FallScreen© is a falls risk calculator and has two forms: a short form and a long form. The short form is designed as a screening instrument suitable for General Practice surgeries, acute hospitals, and long-term care institutions. It takes only 15 minutes to administer and contains five items: a single assessment of vision, peripheral sensation, lower limb strength, reaction time and body sway.
The long form is designed as a comprehensive instrument suitable for Rehabilitation and Physical Therapy and Occupational Therapy settings and for dedicated Falls Clinics. It takes 45 minutes to administer and contains 15 items: three assessments of vision (high and low contrast visual acuity and edge contrast sensitivity), three assessments of peripheral sensation (tactile sensitivity, vibration sense and proprioception), assessments of three lower limb muscle groups (knee extensors, knee flexors and ankle dorsiflexors), assessments of both hand and foot reaction time and four assessments of body sway (sway on floor and foam with eyes open and closed).
Prof Stephen Lord’s Physiological Profile Assessment (PPA) has been marketed through Neuroscience Research Australia (formerly the Prince of Wales Medical Research Institute) as POWMRI FallScreen®. These tools are now used in over 150 research and clinical settings within Australia and across the world, Belgium, Canada, China, Denmark, Finland, Korea, Malta, New Zealand, Norway, Poland, Singapore, Sweden, Switzerland, Taiwan, USA and UK.
Short version: $4,000 (excl. GST). Delivery cost upon request.
Long version: $8000 (excl GST). Delivery cost upon request.
Visual function is measured using a dual contrast visual acuity chart, the “Melbourne Edge Test” and a device for measuring depth perception. Lower limb sensation is assessed with tests of proprioception, touch sensitivity and vibration sense. The strength of three muscle groups in both legs is measured: the knee flexors and extensors and ankle dorsiflexors. Simple reaction time is assessed using movement of the finger as the response, and choice reaction time is assessed using a step as the response. Body sway on a firm and compliant (foam rubber) surface with eyes open is assessed using a swaymeter that measures displacements of the body at the level of the waist.
These assessments are simple, ‘low-tech’ and readily accepted by older subjects. All have high external validity and test-retest reliability and are described in detail in our published papers (1-7). When combined in multivariate discriminant analyses, we have found that these tests can predict those at risk of falling with 75% accuracy in both community and institutional settings.
Short form tests
The FallScreen© internet program
For both the short and long forms, a computer software program assess each person’s performance in relation to the normative database complied from large population studies (6,7). The program produces a falls risk assessment report for each subject which includes the following four components:
The graph indicating the person’s overall falls risk score is a single index score based on a discriminant function analysis developed for our research studies which accurately discriminates between elderly fallers and non-fallers. This graph presented the person’s falls risk score in relation to persons of the same age and in relation to falls risk criteria ranging from low to extreme.
The profile of test performance results presents the subject’s scores in each of the tests in standard (z score) format. As the scores have been standardised the test results can be compared with each other. The table indicting individual test performances in relation to age-matched norms also identifies deficit areas.
Finally, the written report summarises the findings and makes individual recommendations for reducing falls risk. It provides an excellent basis for targeting interventions to improve or compensate for impairments in the following physiological domains: strength, balance, speed and co-ordination, vision, peripheral sensation and therefore reduce the risk of falling in older people.
Click here to log into the Fallscreen© website
NB: By accessing this software, you acknowledge that you have read, understood and agree to the Terms of Sale and Licence Agreementaccompanying this software.
How to obtain a license to use FallScreen©
For information about obtaining the test devices, instructor training and internet access to FallScreen©, email: email@example.com. Click here for more details about falls assessment kits.
Access to the previous Fallscreen© website
As of mid 2013 the previous Fallscreen© website has been deprecated. Access to the previous website is still temporarily avaliable. Please note that it is not recommended that you continue to use the previous website as it may be removed at any time. It is recommended that you export all of your existing data from the previous website as soon as possible.
A summary of this research and a demonstration of FallsScreen can be found in the following paper: Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Physical Therapy 2003;83:237-252. PDF
In April 2017 NeuRA Senior Principal Research Fellow, George Paxinos received an honorary doctorate from the Ionian University, in Corfu, Greece for his landmark work on ‘Mapping the Brain’. Prof George Paxinos paved the way for future neuroscience research by being the first to produce accurate three-dimensional (stereotaxic) framework for placement of electrodes and injections in the brain of experimental […]
To assess measures of postural stability in a large population of persons aged over 60 years in order to compare performance between fallers and non-fallers and relate postural stability to fracture prevalence. Tests of postural stability can identify, independently of age, individuals living in the community who are at risk of falls and fall-related fractures.
To determine the prevalence of impaired vision, peripheral sensation, lower limb muscle strength, reaction time, and balance in a large community-dwelling population of women aged 65 years and over, and to determine whether impaired performances in these tests are associated with falls. These findings support previous results conducted in retirement village and institutional setting and indicate that the test procedure aids in the identification of older community-dwelling women at risk of falls.
A 1-year prospective study was conducted in an intermediate care institution to determine whether a combined assessment of physiological and clinical measures discriminates between elderly fallers and elderly nonfallers. Seventy persons aged between 72 and 96 years (mean 85.6), who were generally independent in activities of daily living, took part in the study, and 66 were available to follow-up. In the follow-up year, 24 subjects experienced no falls, 20 subjects fell one time only and 22 residents fell on two or more occasions. Discriminant analysis identified reaction time, body sway, quadriceps strength, tactile sensitivity, gait impairment, cognitive impairment, psychoactive drug use and age as the variables that significantly discriminated between subjects who experienced falls and those who did not. This procedure correctly classified 86% of subjects into faller and nonfaller groups. These findings suggest that an assessment that combines physiological and clinical factors provides excellent discrimination between elderly fallers and nonfallers.